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Data Engineering

Master Spark, Airflow, Kafka, and the modern data stack

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Duration

10 weeks

Format

Live + Offline

Projects

10+ Hands-on

Difficulty

Intermediate

What You'll Learn

Master Apache Spark and PySpark for big data processing

Build production-grade data pipelines with Apache Airflow

Implement real-time streaming with Apache Kafka

Design scalable ETL/ELT workflows with AWS data services

Use modern data stack tools (dbt, Snowflake, Fivetran, Great Expectations)

Implement data quality testing and monitoring frameworks

Total: 80+ problems

Note: Curriculum may vary based on cohort progress and student needs. All enrolled students get lifetime access to course materials and recordings.

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